This paper presents an approach to evaluate complexity by means of a Natural Language Fuzzy Grammar. Frequently, Linguistics has described a natural language grammar by means of discrete terms. However, a grammar can be explained in terms of degrees by following the concepts of linguistic gradience & fuzziness. Understanding a grammar as a fuzzy or gradient object allows us to establish degrees of grammaticality for every linguistic input. This shall be meaningful for linguistic complexity considering that the less grammatical an input is the more complex its processing will be. From this regard, an input’s degree of complexity is always going to depend on its grammar. The bases of the natural language fuzzy grammar are shown here. Some of these are described by Fuzzy Type Theory. The linguistic inputs are characterized by constraints through a Property Grammar.
CITATION STYLE
Urrutia, A. T. (2019). An approach to measuring complexity within the boundaries of a natural language fuzzy grammar. In Advances in Intelligent Systems and Computing (Vol. 801, pp. 222–230). Springer Verlag. https://doi.org/10.1007/978-3-319-99608-0_25
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